Embrace machine learning approaches and Python to enable automatic rendering of rich insights and solve business problems. The book uses a hands-on case study-based approach to crack real-world applications to which machine learning concepts can be applied. These smarter machines will enable your business processes to achieve efficiencies on minimal time and resources.
Python Machine Learning Case Studies takes you through the steps to improve business processes and determine the pivotal points that frame strategies. You’ll see machine learning techniques that you can use to support your products and services. Moreover you’ll learn the pros and cons of each of the machine learning concepts to help you decide which one best suits your needs.
By taking a step-by-step approach to coding in Python you’ll be able to understand
the rationale behind model selection and decisions within the machine learning process. The book is equipped with practical examples along with code snippets to ensure that you understand the data science approach to solving real-world problems.
What You Will Learn
Gain insights into machine learning concepts
Work on real-world applications of machine learning
Learn concepts of model selection and optimization
Get a hands-on overview of Python from a machine learning point of view
Who This Book Is For
Data scientists, data analysts, artificial intelligence engineers, big data enthusiasts, computer scientists, computer sciences students, and capital market analysts.
Deep Learning with Python: A Hands-on Introduction
Discover the practical aspects of implementing deep-learning solutions using the rich Python ecosystem. This book bridges the gap between the academic state-of-the-art and the industry state-of-the-practice by introducing you to deep learning frameworks such as Keras, Theano, and Caffe. The practicalities of these frameworks is often...
Daniel Arbuckle's Mastering Python
Covers the latest and advanced concepts of Python such as parallel processing with Python 3.6
Explore the Python language from its basic installation and setup to concepts such as reactive programming and microservices
Get introduced to the mechanism for rewriting code in a
Building Machine Learning Systems with Python - Second Edition
Get more from your data through creating practical machine learning systems with Python
About This Book
Build your own Python-based machine learning systems tailored to solve any problem
Discover how Python offers a multiple context solution for create machine learning systems
Blockchain Basics: A Non-Technical Introduction in 25 Steps
In 25 concise steps, you will learn the basics of blockchain technology. No mathematical formulas, program code, or computer science jargon are used. No previous knowledge in computer science, mathematics, programming, or cryptography is required. Terminology is explained through pictures, analogies, and metaphors.
Financial Instrument Pricing Using C++ (The Wiley Finance Series)
The goal of this book is to model financial instruments, such as options, bonds and interest-rate products by partial differential equations, finite differences and C++. It is intended for IT and quantitative finance professionals who know this material and wish to deepen their knowledge and for those readers who use...